Face Detection of Video Image Sequence Based on Human Characteristics

Yansong Liu, Yao Zhao, Zhenqiang Mi
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引用次数: 0

Abstract

The study uses DSP as the core and develops agile tracking and surveillance system. It includes overall design of the system, construction of the hardware and compilation of the software. The system hardware consists of DC, color camera, cradle head, SEED-VPM642 DSP development board or pan-tilt-zoom control system. The paper analyzes com- mon algorithms of motion target detection. According to the characteristics of the acquired video images and the real-time requirements of the system, based on adjacent frame difference, the paper proposes continuous three-frame image differ- ence method to detect moving objects and uses centroid algorithm as the core algorithm of human motion tracking. The paper uses the character of human complexion and applies face detection algorithm based on complexion, which can rap- idly and accurately get the cleat face information of moving people. And the study selects the sum of the absolute value of gray difference as automatic focusing evaluation function of the design. Optimizing common focusing mountain-climb searching algorithm makes the system focus rapid and reliable, which can achieve the objective of automatic detection and trace on moving body and human head location.
基于人的特征的视频图像序列人脸检测
本研究以DSP为核心,开发了敏捷跟踪监控系统。包括系统的总体设计、硬件的构建和软件的编译。系统硬件由直流、彩色摄像机、云台、SEED-VPM642 DSP开发板或平移变焦控制系统组成。分析了常用的运动目标检测算法。根据采集视频图像的特点和系统的实时性要求,本文提出了基于相邻帧差的连续三帧图像差检测运动物体的方法,并以质心算法作为人体运动跟踪的核心算法。本文利用人体肤色的特点,应用基于肤色的人脸检测算法,能够快速、准确地获取运动人群清晰的人脸信息。并选择灰度差绝对值之和作为设计的自动聚焦评价函数。通过对常用对焦爬山搜索算法的优化,使系统对焦快速、可靠,实现了对运动身体和人头定位的自动检测和跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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